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The current study aims to examine if the internal marketing and employees’ personal traits can predict their green innovative behavior at the workplace.

A survey was conducted with 683 frontline employees working in four- and five-star hotels in Serbia. Zero-order bivariate correlations among variables and linear multiple regression were conducted to predict green innovative behavior based on internal marketing, personality traits and psychological capital. Binary genetic algorithms were used to segregate the subset of predictors that would be most suitable to describe variance in the outcome.

The results showed that internal communication, incentive and reward systems, work support, work environment, openness and creative self-efficacy were the most important predictors of almost all the phases of green innovative behavior.

The research showed that a multidimensional approach in analyzing green innovative behavior is necessary as some factors can be significant or not so significant predictors. Acknowledging that innovation is a multistage process, entailing distinct activities and requiring varied individual behaviors to accomplish each task, amplifies the importance of this inquiry. Employees’ personal characteristics have direct impact on green innovative behavior in hospitality. Further, the results gave an insight into the possible mix of elements of internal marketing that can be used for boosting employees’ green innovative behavior in hospitality. This is important as implementing effective internal marketing practices empowers organizations to motivate employees to invest discretionary efforts.

本研究旨在探讨内部营销和员工个人特质是否能预测他们在工作场所的绿色创新行为。

在塞尔维亚的四星和五星级酒店中, 对683名一线员工进行了调查。在变量之间进行了零阶双变量相关性和线性多元回归, 以预测基于内部营销、个性特质和心理资本的绿色创新行为。使用二元遗传算法(GAs)将适用于描述结果变异性的预测子集进行分离。

结果显示, 内部沟通、激励和奖励制度、工作支持、工作环境、开放性和创造力自效能是几乎所有绿色创新行为阶段的最重要的预测因素。

研究表明, 分析绿色创新行为需要采用多维度的方法, 因为某些因素可能是更或更少决定性的预测因素。承认创新是一个多阶段的过程, 涉及到不同的活动, 并要求采用不同的个体行为来完成每个任务, 这加强了对这一调查的重要性。员工的个人特征直接影响了酒店业的绿色创新行为。此外, 结果揭示了可以用于促进酒店业员工绿色创新行为的内部营销元素可能的混合。这是重要的, 因为实施有效的内部营销实践使组织能够激励员工投入可自由支配的努力。

El presente estudio examina si el marketing interno y los rasgos de personalidad de los empleados pueden predecir su comportamiento innovador ecológico en el lugar de trabajo.

Se realizó una encuesta a 683 empleados de primera línea que trabajan en hoteles de cuatro y cinco estrellas en Serbia. Se llevaron a cabo correlaciones bivariadas de orden cero y regresiones lineales múltiples (LM) para predecir el comportamiento innovador ecológico en función del marketing interno, los rasgos de personalidad y el capital psicológico. Se utilizaron algoritmos genéticos binarios (AGs) para segregar el subconjunto de predictores más adecuado para describir la variabilidad en el resultado.

Los resultados mostraron que la comunicación interna, los sistemas de incentivos y recompensas, el apoyo en el trabajo, el entorno laboral, la apertura y la autoeficacia creativa eran los predictores más importantes en casi todas las fases del comportamiento innovador ecológico.

La investigación demostró que es necesario un enfoque multidimensional para analizar el comportamiento innovador ecológico, ya que algunos factores pueden o no ser predictores significativos. Reconocer que la innovación es un proceso de múltiples etapas, que implica actividades distintas y requiere comportamientos individuales variados para realizar cada tarea, amplifica la importancia de esta investigación. Las características personales de los empleados influyen directamente en el comportamiento innovador ecológico en la industria hotelera. Además, los resultados ofrecen una visión de la posible combinación de elementos de marketing interno que se pueden utilizar para impulsar el comportamiento innovador ecológico de los empleados en la hotelería. Esto es importante ya que la implementación de prácticas eficaces de marketing interno permite a las organizaciones motivar a los empleados para que inviertan esfuerzos discrecionales.

The purpose of this study is to examine the impact of the use of Quick Response (QR) code application among the tourists on their satisfaction at a destination regarding information about restaurants’ offer.

A quantitative method was implemented in this study. The field study was conducted in 2019 in the two most visited urban destinations in Serbia. The proposed model was examined using partial least squares, and the model fits, composite reliability and convergent validity were assessed. The direction and significance of the relationships were determined by testing all of the hypotheses.

The results showed that there was a positive effect of using QR codes. However, the study showed that a QR code cannot completely affect the overall satisfaction at a destination. The analysis of the control variables (age and economic status) showed that individual, demographic and economic factors must be taken into consideration to predict individuals’ behaviour.

To enable the generalization of the results, it is advised to conduct research on cross-cultural levels. Future studies related to the topic could be conveyed in other forms of tourism, as well as in other industries, which would provide a better insight into the application of this technology in the future.

The study enables managers of tourism businesses, especially in hospitality, to better understand the importance of the use of a QR code at a destination as an important marketing tool for getting information, and thus to satisfy guests’ expectations.

This study aims to offer insights into a sounder understanding of tourist behavior and travel patterns by systematically identifying psychological manifestations reflected in the basic human value system in the pandemic-induced environment.

A large random sample (49,519 respondents from 29 European countries), generated from the core module Round 9 of the European Social Survey, was used. A post-COVID-19 psychological travel behavior model was constructed by using 12 variables within two opposing value structures (openness to change versus conservatism), shaping specific personalities.

Four types of tourists were identified by using K-means cluster analysis (risk-sensitive, risk-indifferent, risk-tolerant and risk-resistant). The risk-sensibility varied across the groups and was influenced by socio-demographic characteristics, economic status and even differed geographically among nations and traveling cultures.

First, data were collected before the pandemic and did not include information on tourism participation. Second, the model was fully driven by internal factors – motivation. Investigation of additional variables, especially those related to socialization aspects, and some external factors of influence on travel behaviors during and after the crisis, will provide more precise scientific reasoning.

The model was upgraded to some current constructs of salient short-term post-COVID-19 travel behavior embedded in the core principles of universal human values. By separating specific segments of tourists who appreciate personal safety and conformity, from those sharing the extensive need for self-direction and adventure, the suggested model presents a strong background for predicting flows in the post-COVID-19 era.

The technology readiness and acceptance model were mostly employed as theoretical bases to analyze tourist behaviors of adoption of innovative technologies that are part of the smart tourism offer. This study attention now turns to the field of smart tourism human resource management and tries to establish a model to explain the relationship between general dimensions of personality with systematic specific dimensions toward ICT acceptance.

The authors adopted the TRAM model as a way to better understand and evaluate the causal relationships between the personality dimensions, factors of perception, attitudes and behavior of users regarding the acceptance and use of innovative technologies. Based on the empirical data of 478 employees operating in tourist organizations, travel agencies and hotels, the authors employed regression analysis as the basic method for examining the research hypotheses and causal relationships between variables in the presented model.

The analysis revealed that employees in the tourism sector are inclined to adopt new technology, and that technological readiness has an impact on attitudes and intentions toward the use of technologies. Moreover, the results show that the path between the dimensions of technological readiness and intention to use technologies is to a certain extent mediated through perceived ease of use and perceived usefulness.

This research is among the first empirical studies that examine technology readiness and adoption in the context of smart tourism development. Besides the findings extend the literature on the mediating effect of perceived usefulness and perceived ease of use between technology readiness index and technology acceptance behavior.

The aim of the research was to analyse the image of Vojvodina's cuisine and tourist satisfaction with food experience as part of a rural tourism offer in Vojvodina province (Serbia). This chapter is based on research carried out among 891 foreign tourists who visited villages in Vojvodina. The obtained results were examined via exploratory factor analysis, confirmatory factor analysis, multiple regression analysis (stepwise method) and T-test. The obtained results indicated that factors like food uniqueness and cultural heritage, food quality and price, nutrition and health benefits of food and affective image of food influence the image of local cuisine. The results showed that local cuisine (food) can serve as a tool for building destination's brand identity. The study pointed out the role and significance of the image of local cuisine on rural tourist attractions but also on tourist satisfaction with food experience. Also, the contribution of the research is reflected in three aspects: theoretical implication, methodological and practical contribution.